subfits
Extract List of Individual Point Process Models
Takes a Gibbs point process model that has been fitted to several point patterns simultaneously, and produces a list of fitted point process models for the individual point patterns.
Usage
subfits(object, what="models", verbose=FALSE) subfits.old(object, what="models", verbose=FALSE) subfits.new(object, what="models", verbose=FALSE)
Arguments
 object

An object of class
"mppm"
representing a point process model fitted to several point patterns.  what

What should be returned.
Either
"models"
to return the fitted models, or"interactions"
to return the fitted interactions only.  verbose
 Logical flag indicating whether to print progress reports.
Details
object
is assumed to have been generated by
mppm
. It represents a point process model that has been
fitted to a list of several point patterns, with covariate data.
For each of the individual point pattern
datasets, this function derives the corresponding fitted model
for that dataset only (i.e. a point process model for the $i$th
point pattern, that is consistent with object
).
If what="models"
,
the result is a list of point process models (a list of objects of class
"ppm"
), one model for each point pattern dataset in the
original fit.
If what="interactions"
,
the result is a list of fitted interpoint interactions (a list of
objects of class
"fii"
).
Two different algorithms are provided, as
subfits.old
and subfits.new
.
Currently subfits
is the same as the old algorithm
subfits.old
because the newer algorithm is too memoryhungry.
Value

A list of point process models (a list of objects of class
"ppm"
) or a list of fitted interpoint interactions (a list of
objects of class "fii"
).
References
Baddeley, A., Rubak, E. and Turner, R. (2015) Spatial Point Patterns: Methodology and Applications with R. London: Chapman and Hall/CRC Press.
See Also
Examples
H < hyperframe(Wat=waterstriders)
fit < mppm(Wat~x, data=H)
subfits(fit)
H$Wat[[3]] < rthin(H$Wat[[3]], 0.1)
fit2 < mppm(Wat~x, data=H, random=~1id)
subfits(fit2)